# Lemmatization as a Classification Task: Results from Arabic across Multiple Genres

arXiv: https://arxiv.org/abs/2506.18399 · HTML: https://mlsanity.com/paper/2506.18399/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 18 of its 50 references that are in the map.
- First posted on arXiv 23 Jun 2025.

## Builds on (most cited first, 18 of 18)

- [Towards General Text Embeddings with Multi-stage Contrastive Learning](https://mlsanity.com/paper/2308.03281/) (2023)
- [SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings](https://mlsanity.com/paper/2004.08728/) (2020)
- [The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models](https://mlsanity.com/paper/2103.06678/) (2021)
- [Linguistic Input Features Improve Neural Machine Translation](https://mlsanity.com/paper/1606.02892/) (2016)
- [Automatic Error Type Annotation for Arabic](https://mlsanity.com/paper/2109.08068/) (2021)
- [Nematus: a Toolkit for Neural Machine Translation](https://mlsanity.com/paper/1703.04357/) (2017)
- [Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects](https://mlsanity.com/paper/2110.06852/) (2021)
- [Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging](https://mlsanity.com/paper/1910.02267/) (2019)
- [LDC Arabic Treebanks and Associated Corpora: Data Divisions Manual](https://mlsanity.com/paper/1309.5652/) (2013)
- [Camelira: An Arabic Multi-Dialect Morphological Disambiguator](https://mlsanity.com/paper/2211.16807/) (2022)
- [LemmaTag: Jointly Tagging and Lemmatizing for Morphologically-Rich Languages with BRNNs](https://mlsanity.com/paper/1808.03703/) (2018)
- [Arabic Diacritics in the Wild: Exploiting Opportunities for Improved Diacritization](https://mlsanity.com/paper/2406.05760/) (2024)
- [A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment](https://mlsanity.com/paper/2502.13520/) (2025)
- [Joint Lemmatization and Morphological Tagging with LEMMING](https://mlsanity.com/paper/2405.18308/) (2024)
- [Build Fast and Accurate Lemmatization for Arabic](https://mlsanity.com/paper/1710.06700/) (2017)
- [Guidelines for Fine-grained Sentence-level Arabic Readability Annotation](https://mlsanity.com/paper/2410.08674/) (2024)
- [Nefnir: A high accuracy lemmatizer for Icelandic](https://mlsanity.com/paper/1907.11907/) (2019)
- [A Lemma Based Evaluator for Semitic Language Text Summarization Systems](https://mlsanity.com/paper/1403.5596/) (2014)

## Abstract (arXiv)

Lemmatization is crucial for NLP tasks in morphologically rich languages with ambiguous orthography like Arabic, but existing tools face challenges due to inconsistent standards and limited genre coverage. This paper introduces two novel approaches that frame lemmatization as classification into a Lemma-POS-Gloss (LPG) tagset, leveraging machine translation and semantic clustering. We also present a new Arabic lemmatization test set covering diverse genres, standardized alongside existing datasets. We evaluate character level sequence-to-sequence models, which perform competitively and offer complementary value, but are limited to lemma prediction (not LPG) and prone to hallucinating implausible forms. Our results show that classification and clustering yield more robust, interpretable outputs, setting new benchmarks for Arabic lemmatization.